A Lorentz Force-Based SH-typed Electromagnetic Acoustic Transducer Using Flexible Circumferential Printed Circuit
Ultrasonics(2024)
Hangzhou City Univ
Abstract
Structural health monitoring (SHM) of in-service structures is becoming increasingly important. The fundamental shear horizontal (SH0) guided wave mode in plate-like structures shows great potential in damage detection due to its non-dispersive and in-plane vibration properties. In order to generate SH0 waves, a practical Lorentz force-based electromagnetic acoustic transducer (EMAT) was introduced in this study using the flexible circumferential printed circuit (CPC). The designed principle of CPC-EMAT was similar to that of the circumferential magnet array (CMA)-based EMAT. However, the structure of the CMA-EMAT is complex, and it is difficult to assemble for generating high frequency and uniformly distributed omnidirectional SH0 waves. Firstly, the performance of the CMA-EMAT with different numbers of magnets was investigated by finite element simulations. Then, the CPC was proposed to replace the CMA with an optimized designed on its size. The CPC-EMAT is easier to fabricate compared to the CMA-EMAT. Finally, experimental tests were conducted for systematic validations on the transducer properties. Simulation and experimental results show that the CPC-EMAT can successfully generate the desirable and acceptable omnidirectional SH0 waves. The proposed CPC-EMAT is anticipated to find widespread application in SH-typed guided wave-based SHM.
MoreTranslated text
Key words
SH-typed guided waves,Electromagnetic acoustic transducer,Flexible circumferential printed circuit,Lorentz force
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined